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Multiple Regression in Behavioral Research
This text adopts a data-analysis approach to multiple regression. The author integrates design and analysis, and emphasises learning by example and critiquing published research.
Measurement, Design, and Analysis
In textbooks and courses in statistics, substantive and measurement issues are rarely, if at all, considered. Similarly, textbooks and courses in measurement virtually ignore design and analytic questions, and research design textbooks and courses pay little attention to analytic and measurement issues. This fragmentary approach fosters a lack of appreciation of the interrelations and interdependencies among the various aspects of the research endeavor. Pedhazur and Schmelkin's goal is to help readers become proficient in these aspects of research and their interrelationships, and to use that information in a more integrated manner. The authors offer extensive commentaries on inputs and outputs of computer programs in the context of the topics presented. Both the organization of the book and the style of presentation allow for much flexibility in choice, sequence, and degree of sophistication with which topics are dealt.
Multiple Regression and Beyond
Companion Website materials: https://tzkeith.com/ Multiple Regression and Beyond offers a conceptually-oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae, this book introduces material to students more clearly, and in a less threatening way. In addition to illuminating content necessary for coursework, the accessibility of this approach means students are more likely to be able to conduct research using MR or SEM--and more likely to use the methods wisely. This boo...
Liberalism and Conservatism
Originally published in 1984, this book proposes a structural theory of social attitudes, presents the empirical evidence for the theory, and defines and explores liberalism and conservatism and the justification for associating social attitudes with these terms. The core ideas are that the structure of social attitudes, those sets of beliefs about social "objects" or referents shared by many or most people of a society, is basically dualistic rather than bipolar, and that the referents of social attitudes are differentially criterial to individuals and groups of individuals. The common belief that social attitudes are polarized, with liberal beliefs at once end of a continuum and conservative beliefs at the other end, is questioned. Instead, liberalism and conservatism are conceived as separate and independent sets of beliefs. The book will elaborate and explain these statements and bring evidence to bear on the empirical validity.
Reading Statistics and Research
This text explains to consumers of research how to read, understand, and critically evaluate the statistical information contained in technical research reports. Excerpts from over 500 recent research articles are presented and discussed to illustrate concepts.
Transformers
Recent catastrophic blackouts have exposed major vulnerabilities in the existing generation, transmission, and distribution systems of transformers widely used for energy transfer, measurement, protection, and signal coupling. As a result, the reliability of the entire power system is now uncertain, and many blame severe underinvestment, aging technology, and a conservative approach to innovation. Composed of contributions from noted industry experts around the world, Transformers: Analysis, Design, and Measurement offers invaluable information to help designers and users overcome these and other challenges associated with the design, construction, application, and analysis of transformers. ...
Statistics for the Social Sciences
Written by a quantitative psychologist, this textbook explains complex statistics in accessible language to undergraduates in all branches of the social sciences. Built around the central framework of the General Linear Model (GLM), Statistics for the Social Sciences teaches students how different statistical methods are interrelated to one another. With the GLM as a basis, students with varying levels of background are better equipped to interpret statistics and learn more advanced methods in their later courses. Russell Warne makes statistics relevant to students' varying majors by using fascinating real-life examples from the social sciences. Students who use this book will benefit from clear explanations, warnings against common erroneous beliefs about statistics, and the latest developments in the philosophy, reporting and practice of statistics in the social sciences. The textbook is packed with helpful pedagogical features including learning goals, guided practice and reflection questions.
Regression Analysis and Linear Models
Ephasizing conceptual understanding over mathematics, this user-friendly text introduces linear regression analysis to students and researchers across the social, behavioral, consumer, and health sciences. Coverage includes model construction and estimation, quantification and measurement of multivariate and partial associations, statistical control, group comparisons, moderation analysis, mediation and path analysis, and regression diagnostics, among other important topics. Engaging worked-through examples demonstrate each technique, accompanied by helpful advice and cautions. The use of SPSS, SAS, and STATA is emphasized, with an appendix on regression analysis using R. The companion websi...
The SAGE Dictionary of Statistics
The SAGE Dictionary of Statistics provides students and researchers with an accessible and definitive resource to use when studying statistics in the social sciences, reading research reports and undertaking data analysis.
Measurement, Design, and Analysis
In textbooks and courses in statistics, substantive and measurement issues are rarely, if at all, considered. Similarly, textbooks and courses in measurement virtually ignore design and analytic questions, and research design textbooks and courses pay little attention to analytic and measurement issues. This fragmentary approach fosters a lack of appreciation of the interrelations and interdependencies among the various aspects of the research endeavor. Pedhazur and Schmelkin's goal is to help readers become proficient in these aspects of research and their interrelationships, and to use that information in a more integrated manner. The authors offer extensive commentaries on inputs and outputs of computer programs in the context of the topics presented. Both the organization of the book and the style of presentation allow for much flexibility in choice, sequence, and degree of sophistication with which topics are dealt.
